In recent years, the phenomenon of “negative electricity prices” has increasingly appeared in the electricity market, particularly in Shandong and Zhejiang. In January of this year, Zhejiang’s electricity market experienced negative prices for two consecutive days, leading to widespread discussions about “paying to use electricity.” This has raised concerns about the future of renewable energy development in China. To address these issues, on March 12, a reporter from Zhongneng Media interviewed Pan Yuelong, the Chairman of the Supervisory Board of the China Electricity Council.
Chairman Pan believes that: 1. The emergence of negative electricity prices is an objective phenomenon brought about by the increasing penetration of renewable energy and the clearing mechanism of the electricity market. 2. The marketization process has led to a coexistence of negative and high electricity prices. 3. The short-term clearing of negative electricity prices in the electricity market does not equate to settled negative prices, and it is essential to approach this matter with a rational and objective perspective, avoiding excessive interpretation.
Regarding the full entry of renewable energy into the market, he suggests optimizing and improving three key areas: First, continuously refining the electricity market trading rules to accommodate the characteristics of renewable energy and enhancing the long-term electricity trading contract mechanism. Second, strengthening the coordinated development of energy storage and renewable energy. Third, enhancing the collaborative planning between renewable energy and load sides.
Q: How do negative electricity prices occur, and are they a normal phenomenon in electricity market operations?
A: The appearance of negative electricity prices in the electricity market is not uncommon globally. Different markets exhibit variations in rules flexibility, regulation capacity, and cross-regional collaboration, leading to distinct spatial and temporal characteristics of negative pricing. For example, in Germany’s electricity market in spring 2024, during a windy period, wind power accounted for 25% of production, with negative prices reaching as low as -80 euros per megawatt-hour for a duration of 6 hours. In California, in March 2024, with solar power contributing 30% and only 4% energy storage, negative prices persisted for five consecutive days during peak solar output hours, highlighting localized supply and demand dynamics.
In China, with the rapid development of renewable energy and the acceleration of the electricity market’s construction, short-term signals reflecting market supply and demand are becoming more apparent. For instance, during the Spring Festival from January 19 to 20, 2025, due to a 30% drop in industrial load in Zhejiang while renewable capacity reached 56.82 million kilowatts (including 47.27 million kilowatts of solar), negative prices of -20 yuan per megawatt-hour were recorded for two consecutive days. Similarly, during the May Day holiday in 2023, Shandong experienced negative electricity prices for 22 consecutive hours, reaching a minimum of -85 yuan per megawatt-hour, with solar energy accounting for 22.5% of production.
From these examples, we can observe patterns in negative pricing. Temporal factors indicate that negative prices frequently occur during high-production periods for wind and solar energy and during holiday load valleys. The highest output periods for solar energy typically align with midday peaks, while nighttime wind peaks also contribute to these occurrences. Spatially, regions with higher renewable energy penetration experience negative prices more frequently, and the market’s tolerance for negative pricing directly influences its ability to reflect changes in supply and demand.
Overall, the emergence of negative electricity prices is a direct consequence of the increasing penetration of renewable energy and the electricity market’s clearing mechanism. Marketization has led not only to negative prices but also to a simultaneous existence of both negative and high prices, which indicates the unique supply and demand dynamics of electricity as a commodity. Therefore, the short-term clearing of negative electricity prices should not be interpreted as settled negative prices; a rational and objective approach is necessary.
Q: What market signals do negative prices convey?
A: Fundamentally, negative electricity prices represent an external manifestation of the long-term mismatch between the power supply structure and load demand within the electricity system. They act as a “whistleblower,” promptly reflecting structural issues in the system. Despite the call for “optimizing the layout of renewable energy” in the “14th Five-Year Plan for Modern Energy System” issued by nine government departments in 2022, a persistent mindset of prioritizing resource development over system adaptation has led to significant oversupply during peak production periods, eventually reflected in negative prices.
The occurrence of negative prices highlights the need for an optimized investment layout in renewable energy generation. Although negative prices are a normal phenomenon during market construction, they also indicate a state of short-term supply-demand imbalance within the power system, warranting careful attention. Different scenarios necessitate distinct analyses of system imbalances. Short-term negative prices are often triggered by extreme weather or sudden load fluctuations, indicating that the system’s flexible adjustment capacity may be nearing its limits. Prolonged periods of negative pricing suggest a rigid oversupply, necessitating vigilance regarding the utilization rates of cross-regional transmission channels and traditional power source adjustments. Frequent and prolonged occurrences of negative prices signal structural contradictions within the market, such as rapid renewable energy development, a lack of flexible resources, and inadequacies in demand-side response mechanisms.
To address these challenges, it is crucial to expedite the establishment of a price signal response mechanism, enabling market optimization to allocate resources effectively, encourage the active and efficient participation of adjustable resources, and promote the high-quality sustainable development of renewable energy.
Q: What insights can we draw from the emergence of negative prices for the development of renewable energy in China? What recommendations do you have following the full market entry of renewable energy?
A: Against the backdrop of “dual carbon” goals, China’s direction toward a green energy transition remains unchanged, necessitating the promotion of sustainable development in renewable energy while ensuring reasonable returns and guiding expectations through market mechanisms. The fluctuations in market electricity prices post-market entry will impact the operational dynamics of enterprises, closely related to the production characteristics and adjustment capabilities of renewable energy companies.
Solar power generation, constrained by the rigidity of midday output curves, often experiences mismatches during peak solar production and low load periods, requiring energy storage adjustments or hydrogen production to achieve load transfer. Wind power, conversely, faces challenges during nighttime peaks when residential electricity demand is low, necessitating considerations for cross-provincial green electricity trading and demand-side response mechanisms.
Renewable energy generation enterprises should adapt their investment and pricing strategies based on technological differences, optimize supporting facilities such as energy storage, and refine generation curves to leverage advantages amid market price fluctuations. In the current electricity market environment, further integration of project planning, investment, and operations is essential for renewable energy companies. This includes establishing a scientific price elasticity assessment model during planning and investment phases, incorporating market parameters such as regional adjustment capabilities and utilization rates of cross-regional channels into resource development prioritization.
In the operational phase, it is vital to establish a volatility revenue model that utilizes low-cost energy storage during negative price periods and flexibly discharges during high-price periods to achieve revenue balance across time. This will enhance the profitability of renewable energy projects, increase risk resilience, and maintain a dynamic balance between high-quality development and system safety.
The recently issued notice on “Deepening the Market-Oriented Reform of Renewable Energy Grid Pricing to Promote High-Quality Development” emphasizes the importance of integrating renewable energy into market trading to establish price formation through market transactions. Although current electricity price fluctuations, including temporary negative prices, are significant, the transition to green energy remains an inevitable trend in China. As renewable energy enters the market, it is crucial to simultaneously strengthen supporting measures that promote high-quality development, ensuring stable expectations for renewable energy growth.
In summary, optimizing and improving three key areas is recommended: First, continually refining electricity market trading rules to suit renewable energy characteristics and enhancing the long-term trading contract mechanism to allow for more flexible long-term contracts with electricity users and sales companies, thereby reducing risks associated with significant price fluctuations. Second, bolstering the coordinated development of energy storage and renewable energy by increasing support for energy storage technology research and application through financial subsidies and tax incentives, encouraging the construction of energy storage facilities, and establishing operational models that allow storage to participate in ancillary services markets. Third, enhancing the adaptability of the renewable energy system by continuously strengthening collaborative planning between renewable energy and load sides to ensure a better match between renewable projects and load characteristics, utilizing big data and artificial intelligence for accurate forecasting of output and demand.
